Adaptive random testing (ART) describes a family of algorithms for generating random test cases that have been experimentally demonstrated to have greater fault-detection capacity than simple random testing. We outline and demonstrate two new ART algorithms, and demonstrate experimentally that they offer similar performance advantages, with considerably lower overhead than other ART algorithms.